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1.
Best practices for determining resting energy expenditure in critically ill adults.
Schlein, KM, Coulter, SP
Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition. 2014;(1):44-55
Abstract
Indirect calorimetry (IC) is the gold standard for measuring resting energy expenditure (REE) in the critically ill patient. The use of predictive equations to develop nutrition regimens can be problematic in the critical care setting, because the effects that disease, injury, and stress have on REE are often varied and unpredictable. IC testing ensures that the specific conditions of the critically ill patient are taken into account, thereby preventing potential complications from over- and underfeeding. The clinical indications for and appropriate applications of IC testing are discussed. In addition, 3 case studies are presented that highlight the application of IC. The clinician can face numerous obstacles in implementing IC testing, including lack of equipment, staff shortages, and lack of knowledge regarding application and interpretation of the IC study. Recommendations for addressing these challenges are discussed. In addition, guidelines on ordering and interpreting the IC study are provided. Best practices for predictive equations in critically and acutely ill patients are also presented, since IC testing is not feasible in certain situations. Given the importance of predicting REE in the critically ill patient, it is paramount that more healthcare professionals incorporate IC testing into practice. A multidisciplinary approach is helpful in developing a well-established clinical practice. Nutrition support clinicians can promote optimal nutrition management by being well-informed and able to provide evidence-based recommendations for the use of IC.
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2.
Resting energy expenditure of morbidly obese patients using indirect calorimetry: a systematic review.
Kee, AL, Isenring, E, Hickman, I, Vivanti, A
Obesity reviews : an official journal of the International Association for the Study of Obesity. 2012;(9):753-65
Abstract
The increasing proportion of acutely ill hospital patient admissions presenting with a morbidly obese body mass index (BMI ≥ 40 kg m(-2) ) as a comorbidity is an emerging clinical concern. Suboptimal food intake and malnutrition is prevalent in the acute care hospital setting. The energy requirements necessary to prevent malnutrition in acutely ill patients with morbid obesity remains unclear. The aim of this systematic review was to identify studies in the literature that have used indirect calorimetry to measure the resting energy expenditure of patients with morbid obesity to establish their minimum energy requirements and the implications for optimal feeding practices in acutely ill hospitalized patients. A total of 20 studies from PubMed, Cochrane Library and Embase met the inclusion criteria and were reviewed. All articles were graded using the Australian National Health and Medical Research Council levels of evidence and given a quality rating using the American Dietetic Association recommendations. Studies were categorized according to the mean BMI of its subjects. The most commonly measured resting energy expenditures for morbidly obese patients are between 2,000 and 3,000 kcal d(-1) (8,400-12,600 kJ d(-1) ). Activity and injury factors of acutely ill morbidly obese patients could result in significantly greater energy requirements for this patient group and are unlikely to be met by standard hospital menus. Establishing the minimum energy requirements for this population group will help inform adequate and accurate energy provision in the acute setting. Outcomes of underfeeding and overfeeding in morbidly obese patients warrant further research.
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3.
Role of resting metabolic rate and energy expenditure in hunger and appetite control: a new formulation.
Blundell, JE, Caudwell, P, Gibbons, C, Hopkins, M, Naslund, E, King, N, Finlayson, G
Disease models & mechanisms. 2012;(5):608-13
Abstract
A long-running issue in appetite research concerns the influence of energy expenditure on energy intake. More than 50 years ago, Otto G. Edholm proposed that "the differences between the intakes of food [of individuals] must originate in differences in the expenditure of energy". However, a relationship between energy expenditure and energy intake within any one day could not be found, although there was a correlation over 2 weeks. This issue was never resolved before interest in integrative biology was replaced by molecular biochemistry. Using a psychobiological approach, we have studied appetite control in an energy balance framework using a multi-level experimental system on a single cohort of overweight and obese human subjects. This has disclosed relationships between variables in the domains of body composition [fat-free mass (FFM), fat mass (FM)], metabolism, gastrointestinal hormones, hunger and energy intake. In this Commentary, we review our own and other data, and discuss a new formulation whereby appetite control and energy intake are regulated by energy expenditure. Specifically, we propose that FFM (the largest contributor to resting metabolic rate), but not body mass index or FM, is closely associated with self-determined meal size and daily energy intake. This formulation has implications for understanding weight regulation and the management of obesity.
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4.
Evolving concepts on adjusting human resting energy expenditure measurements for body size.
Heymsfield, SB, Thomas, D, Bosy-Westphal, A, Shen, W, Peterson, CM, Müller, MJ
Obesity reviews : an official journal of the International Association for the Study of Obesity. 2012;(11):1001-14
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Abstract
Establishing if an adult's resting energy expenditure (REE) is high or low for their body size is a pervasive question in nutrition research. Early workers applied body mass and height as size measures and formulated the Surface Law and Kleiber's Law, although each has limitations when adjusting REE. Body composition methods introduced during the mid-20th century provided a new opportunity to identify metabolically homogeneous 'active' compartments. These compartments all show improved correlations with REE estimates over body mass-height approaches, but collectively share a common limitation: REE-body composition ratios are not 'constant' but vary across men and women and with race, age and body size. The now-accepted alternative to ratio-based norms is to adjust for predictors by applying regression models to calculate 'residuals' that establish if an REE is relatively high or low. The distinguishing feature of statistical REE-body composition models is a 'non-zero' intercept of unknown origin. The recent introduction of imaging methods has allowed development of physiological tissue-organ-based REE prediction models. Herein, we apply these imaging methods to provide a mechanistic explanation, supported by experimental data, for the non-zero intercept phenomenon and, in that context, propose future research directions for establishing between-subject differences in relative energy metabolism.
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Adaptive alterations in metabolism: practical consequences on energy requirements in the severely ill patient.
Fontaine, E, Müller, MJ
Current opinion in clinical nutrition and metabolic care. 2011;(2):171-5
Abstract
PURPOSE OF REVIEW A recent and large multicentre study reports that ICU patients receive less than half of the recommended energy requirement. This review aims at clarifying whether underfeeding is scientifically justified or sustained by evidence-based medicine. RECENT FINDINGS There is evidence that optimal nutrition improves clinical outcome of critically ill patients. The deleterious effect of overfeeding ICU patients is now well acknowledged, but underfeeding is not scientifically justified in ICU patients. Total energy expenditure in ICU patients is variable and methods to predict resting energy expenditure are questionable in these patients. SUMMARY There is a need to measure energy expenditure in clinical practice. When not possible, the current guidelines on artificial nutrition (i.e. 25 kcal/kg per day) should be applied in order to limit underfeeding.
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Energy balance in patients with pressure ulcers: a systematic review and meta-analysis of observational studies.
Cereda, E, Klersy, C, Rondanelli, M, Caccialanza, R
Journal of the American Dietetic Association. 2011;(12):1868-76
Abstract
Medical nutrition therapy is reported to contribute to wound healing. However, effective intervention requires an accurate estimation of individual energy needs, which, in turn, relies on accurate methods of assessment. The primary aims of this systematic review and meta-analysis were to evaluate the resting energy expenditure (REE) of patients with pressure ulcers (PUs) compared to matched control groups and the potential estimation bias of REE predictive equations. The recommended daily energy requirements of patients with PUs were also assessed, along with their energy balance (daily energy requirement vs intake). All language, original, full-text research articles published between January 1, 1950, and July 31, 2010, were searched through electronic databases. Relevant studies were also identified by reviewing citations. Observational (case-control and case-series) studies providing data on measured REE were initially included. Data extracted were measured REE, predicted REE, and daily energy intake. Five studies were included in the meta-analysis. Compared to controls (n=101), patients with PUs (n=92) presented higher measured REE (weighted mean 20.7±0.8 vs 23.7±2.2 kcal/kg/day; P<0.0001). In these patients, measured REE was also higher than predicted REE (calculated using the Harris-Benedict formula in all studies; 21.0±1.0 kcal/kg/day; P<0.0001), whereas energy intake (n=78; 21.7±3.1 kcal/kg/day) was significantly lower (P<0.0001) than total daily requirement, which was calculated as 29.4±2.7 kcal/kg/day. Patients with PUs are characterized by increased REE and reduced energy intake. In the estimation of REE using the Harris-Benedict formula, a correction factor (×1.1) should be considered to accurately assess energy needs. Moreover, an energy intake of 30 kcal/kg/day seems appropriate to cover the daily requirements of patients with PUs.
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Functional body composition: insights into the regulation of energy metabolism and some clinical applications.
Müller, MJ, Bosy-Westphal, A, Later, W, Haas, V, Heller, M
European journal of clinical nutrition. 2009;(9):1045-56
Abstract
The application of advanced methods and techniques and their continuous development enable detailed body composition analyses (BCAs) and modeling of body composition at different levels (e.g., at atomic, molecular, organ-tissue and whole body level). Functional body composition integrates body components into regulatory systems (e.g., on energy balance). Regulation of body weight is closely linked to the mass and function of individual body components. Fat mass is part of the energy intake regulatory feedback system. In addition, fat-free mass (FFM) and fat mass are both determinants of resting energy expenditure (REE). Up to 80% of the variance in energy intake and energy expenditure is explained by body composition. A deviation from normal associations between body components and function suggests a metabolic disequilibrium (e.g., in the REE-FFM relationship or in the plasma leptin-fat mass association) that may occur in response to weight changes and diseases. The concept of functional body composition adds to a more sophisticated view on nutritional status and diseases, as well as to a characterization of biomedical traits that will provide functional evidence relating genetic variants.
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8.
Gendered dimensions of obesity in childhood and adolescence.
Sweeting, HN
Nutrition journal. 2008;:1
Abstract
BACKGROUND The literature on childhood and adolescent obesity is vast. In addition to producing a general overview, this paper aims to highlight gender differences or similarities, an area which has tended not to be the principal focus of this literature. METHODS Databases were searched using the terms 'obesity' and 'child', 'adolescent', 'teenager', 'youth', 'young people', 'sex', 'gender', 'masculine', 'feminine', 'male', 'female', 'boy' and 'girl' (or variations on these terms). In order to limit the potential literature, the main focus is on other reviews, both general and relating to specific aspects of obesity. RESULTS The findings of genetic studies are similar for males and females, and differences in obesity rates as defined by body mass index are generally small and inconsistent. However, differences between males and females due to biology are evident in the patterning of body fat, the fat levels at which health risks become apparent, levels of resting energy expenditure and energy requirements, ability to engage in certain physical activities and the consequences of obesity for the female reproductive system. Differences due to society or culture include food choices and dietary concerns, overall physical activity levels, body satisfaction and the long-term psychosocial consequences of childhood and adolescent obesity. CONCLUSION This review suggests differences between males and females in exposure and vulnerability to obesogenic environments, the consequences of child and adolescent obesity, and responses to interventions for the condition. A clearer focus on gender differences is required among both researchers and policy makers within this field.
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Computational modeling of cancer cachexia.
Hall, KD, Baracos, VE
Current opinion in clinical nutrition and metabolic care. 2008;(3):214-21
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Abstract
PURPOSE OF REVIEW Measurements of whole-body energy expenditure, body composition, and in-vivo metabolic fluxes are required to quantitatively understand involuntary weight loss in cancer cachexia. Such studies are rare because cancer cachexia occurs near the end of life when invasive metabolic tests may be precluded. Thus, models of cancer-associated weight loss are an important tool for helping to understand this debilitating condition. RECENT FINDINGS A computational model of human macronutrient metabolism was recently developed that simulates the normal metabolic adaptations to semi-starvation and re-feeding. Here, this model was used to integrate data on the metabolic changes in patients with cancer cachexia. The resulting computer simulations show how the known metabolic disturbances synergize with reduced energy intake to result in a progressive loss of body weight, fat mass, and fat-free mass. The model was also used to simulate the effects of nutritional support and investigate inhibition of lipolysis versus proteolysis as potential therapeutic approaches for cancer cachexia. SUMMARY Computational modeling is a new tool that can integrate clinical data on the metabolic changes in cancer cachexia and provide a conceptual framework to help understand involuntary weight loss and predict the effects of potential therapies.
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Energy requirements in frail elderly people: a review of the literature.
Gaillard, C, Alix, E, Sallé, A, Berrut, G, Ritz, P
Clinical nutrition (Edinburgh, Scotland). 2007;(1):16-24
Abstract
This review collates studies of healthy, sick, underweight (BMI < or = 21 kg/m2) and very elderly people (> or = 90 yr), in whom resting energy expenditure (REE) was measured using indirect calorimetry. We have observed the following: (1) REE, when adjusted for differences in both body weight and fat-free mass (FFM), is similar in healthy and in sick elderly people being 20 and 28 kcal/kg of FFM per day, respectively, (2) their nutritional status influences their energy requirements given that weight-adjusted REE increases in line with a decrease in BMI, (3) total energy expenditure is lower in sick elderly people given that their physical activity level, i.e. the ratio of total energy expenditure to REE, is reduced during disease averaging at 1.36, (4) energy intake (EI) being only 1.23 x REE is insufficient to cover energy requirements in sick elderly patients, whereas the EI of healthy elderly people appears sufficient to cover requirements, and finally, (5) gender ceases to be a determinant of REE in people aged 60 yr or over, with the Harris & Benedict equation capable of accurately predicting mean REE in this population, whether healthy or sick.